Users and organizations that deal with significant quantities of digital information often have difficulty managing files and data in an efficient and intuitive manner. An inability to easily store, organize, and locate documents and content, while causing difficulty and irritation at the level of the individual user, may translate into significant inefficiencies and lost opportunities at the organizational level. Lost documents, overlooked e-mails and records, and the duplication of work between users or departments may impact a business's productivity and agility. For the digital consumer, difficulty organizing and locating digital data may result in user frustration and the accidental re-purchasing of extant content.
Modern high-capacity hard drives and remote storage solutions allow for the retention of large numbers of documents and records nearly indefinitely; however, increases in storage capacity have often not been accompanied by a corresponding increase in the effectiveness of document management tools and technology. Most modern storage solutions utilize some combination of a traditional directory-based file system and search-based data management such as full-text search or basic keyword tagging. Although appropriate for some types of data, both types of systems may present significant challenges when dealing with large numbers of files or heterogeneous data sets. Directory-based solutions may be satisfactory for highly structured data or content; however, directory-trees often break down as an organizational method when a document or datum is relevant across one or more data categories or when a user desires to cross-reference or locate documents based on an alternate organizational schema. Simple text and keyword search-based systems generally discard the rigid structure of the directory-tree, but may present other challenges, such as requiring that the user remember specific terms or phrases associated with the document to be located. The lack of structure associated with many keyword or full-text based data management solutions may also pose difficulties when similar keyword terms occur over different classes of documents, such as a “flight” keyword being used both for trip records and engineering documents.
Some of the weaknesses with directory and keyword/text search-based systems may be mitigated by associating one or more elements of typed metadata (e.g. customer ID, band name, product code, etc.) with each piece of data. Although the addition of typed metadata may allow for structured searches and easier access to data, these solutions often require a user to manually enter relevant metadata into a number of fields at the time that the document or data is being stored. In many cases, this process is extremely time consuming and may require that the user sort through a large number of metadata fields, only a fraction of which may be relevant for a particular document. These categories of metadata are often fixed by the storage solution provider and/or selected without a deep understanding of the needs of the user or organization. Still further, many metadata-based storage systems may encounter problems if users are not familiar with organizational or system naming conventions, as the entry of metadata values or terms in dissimilar ways may hamper efficient search. Taken as a whole, these problems often hinder the adoption of metadata-based document management systems, and can lead to a loss in system effectiveness and overall utility. A system capable of leveraging the power of a metadata-based system while preserving qualities such as customizability, consistency, and/or ease of use could provide significant benefits to organizations and individuals working in and interacting with data rich digital environments.